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Maximum likelihood estimation of position in GNSS
Closas Gómez, Pau; Fernández Prades, Carlos; Fernández Rubio, Juan Antonio
Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions; Universitat Politècnica de Catalunya. SPCOM - Grup de Recerca de Processament del Senyal i Comunicacions
In this letter, we obtain the Maximum Likelihood Estimator of position in the framework of Global Navigation Satellite Systems. This theoretical result is the basis of a completely different approach to the positioning problem, in contrast to the conventional two-steps position estimation, consisting of estimating the synchronization parameters of the in-view satellites and then performing a position estimation with that information. To the authors’ knowledge, this is a novel approach which copes with signal fading and it mitigates multipath and jamming interferences. Besides, the concept of Position–based Synchronization is introduced, which states that synchronization parameters can be recovered from a user position estimation. We provide computer simulation results showing the robustness of the proposed approach in fading multipath channels. The Root Mean Square Error performance of the proposed algorithm is compared to those achieved with state-of-the-art synchronization techniques. A Sequential Monte–Carlo based method is used to deal with the multivariate optimization problem resulting from the ML solution in an iterative way.
Peer Reviewed
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal
Artifical satellites in communication
Monte Carlo method
Fading multipath channel
Global navigation satellite systems
GNSS
Interference suppression
Iterative methods
Jamming interferences
Maximum likelihood estimation
Monte Carlo methods
Multipath channels
Multivariate optimization problem
Position measurement
Root mean square error
Synchronization
Satèl.lits artificials en telecomunicació
Monte Carlo, Mètode de
Artículo
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
         

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